Capacity planning for user wait time

ABSTRACT

Systems and methods are disclosed for determining when installation of additional self-service financial transaction devices (SSFTDs) may be desired at a site to improve end-to-end user experience. The system may collect and store transaction-level data, session-level data, user wait time data, and/or other data, and use an enhanced SSFTD user wait time model to identify recommendations and other statistical outputs. The SSFTD may include hardware and software to assist in measuring and collecting various useful readings.

TECHNICAL FIELD

Aspects of the present disclosure relate to a self-service financialtransaction device (SSFTD). More specifically, aspects of the disclosurerelate to modeling and/or modifying a SSFTD to improve end to end userexperience.

BACKGROUND

Customers of financial institution entities regularly fulfill theirbusiness and personal banking needs by conducting transactions throughvarious types of automated and computerized systems. Not only do thesesystems continue to provide fast and efficient alternatives to waitingfor assistance from a customer representative of the entity (e.g., abank teller) when the transaction at hand is relatively simple andstraightforward, such as a cash withdrawal, but such systems have alsoadvanced to where many transactions that can be completed in-person withthe assistance of a customer representative can also be completedwithout the assistance of a customer representative. For example,automated teller machines (ATMs) are able to provide customers (e.g.,users, customers, clients, or individuals) with the ability to withdrawand/or deposit money, request cash advances on one or more credit cards,review and/or print account balances and activity reports, as well asnumerous other transaction types.

With the proliferation of ATMs, financial institutions have been usingaggregated utilization statistics (e.g., what percentage of the time theATM is in use) to determine when additional ATMs are desired at alocation. The ATM utilization model is based on models financialinstitutions have used for capacity planning for full-service bankteller planning. In both instances, while utilization is an indicator ofuser need for more ATMs/tellers at a location, analysis narrowly focusedon utilization fails to address other aspects to be desired.

BRIEF SUMMARY

In light of the foregoing background, the following presents asimplified summary of the present disclosure in order to provide a basicunderstanding of some aspects of the disclosure. This summary is not anextensive overview of the disclosure. It is not intended to identify keyor critical elements of the disclosure or to delineate the scope of thedisclosure. The following summary merely presents some concepts of thedisclosure in a simplified form as a prelude to the more detaileddescription provided below.

Aspects of the present disclosure are directed to a method and systemfor determining when installation of additional self-service financialtransaction devices (SSFTDs) may be desired at a site to improveend-to-end user experience. The system may collect and storetransaction-level data, session-level data, user wait time data, and/orother data, and use an enhanced SSFTD user wait time model to identifyrecommendations and other statistical outputs. The SSFTD may includehardware and software to assist in measuring and collecting varioususeful readings.

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. The summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of aspects of the present disclosure andthe advantages thereof may be acquired by referring to the followingdescription in consideration of the accompanying drawings, in which likereference numbers indicate like features, and wherein:

FIG. 1 illustrates a schematic diagram of a general-purpose digitalcomputing environment in which certain aspects described herein may beimplemented;

FIG. 2 is an illustrative block diagram of workstations and servers thatmay be used to implement the processes and functions of certainembodiments of the present disclosure;

FIG. 3 is an illustrative functional block diagram of a self-servicefinancial transaction device (SSFTD) according to one or more aspectsdescribed herein;

FIG. 4 is a flowchart illustrating an example method performed by aremote computer according to one or more aspects of the presentdisclosure;

FIGS. 5A and 5B illustrate collected data from a single drive-up SSFTDconfiguration;

FIG. 6 illustrates the end-to-end user experience for a SSFTD, includinguser wait time and other times outside of actual machine utilization;and

FIGS. 7 and 8 illustrate sample data points for a SSFTD configuration,where user wait time and other transaction data is collected foranalysis in accordance with aspects of the disclosure.

DETAILED DESCRIPTION

In the following description of various illustrative embodiments,reference is made to the accompanying drawings, which form a parthereof, and in which is shown by way of illustration various embodimentsin which one or more aspects of the disclosure may be practiced. It isto be understood that other embodiments may be utilized and structuraland functional modifications may be made without departing from thescope of the present disclosure.

By way of general introduction, aspects of the disclosure relate toproviding methods and systems for determining when installation ofadditional self-service financial transaction devices (SSFTDs), such asautomated teller machines (ATMs), may be desired at a location/site, andgenerating, by a computer, recommendations/statistics accordingly. Thesystem may include a computer system with one or more memories (e.g.,database, data store, or other means for memory) to storetransaction-level data and other data (e.g., session-level data, or userwait time data) about SSFTDs and an enhanced SSFTD user wait time model(hereinafter referred to as “enhanced model”) to identify appropriaterecommendations and other outputs.

In another aspect of the disclosure, a system may include hardware(e.g., sensors, timers, audio/video recorders, or similar type hardware)and/or software components (e.g., computer-executable instructionsstored on non-transitory, tangible computer-readable media) to assist inmeasuring and collecting various readings relating to variousaspects/factors including, but not limited to, SSFTD utilization, userwait time and usage time, and other factors. The various measurementsmay be used, in some embodiments, to improve the end-to-end userexperience, including optimizing the total time that a user may wait touse a SSFTD. In addition, the measurements collected may be stored in amemory (e.g., database or data store) for further analytics, modeling,and testing.

FIG. 1 illustrates a block diagram of a generic computing device 101(e.g., a computer server) that may be used according to an illustrativeembodiment of the disclosure. The computer server 101 may have aprocessor 103 for controlling overall operation of the server and itsassociated components, including RAM 105, ROM 107, input/output module109, and memory 115.

Input/Output (I/O) 109 may include a microphone, keypad, touch screen,camera, and/or stylus through which a user of device 101 may provideinput, and may also include one or more of a speaker for providing audiooutput and a video display device for providing textual, audiovisualand/or graphical output. Other I/O devices through which a user and/orother device may provide input to device 101 also may be included.Software may be stored within memory 115 and/or storage to provideinstructions to processor 103 for enabling server 101 to perform variousfunctions. For example, memory 115 may store software used by the server101, such as an operating system 117, application programs 119, and anassociated database 121. Alternatively, some or all of server 101computer executable instructions may be embodied in hardware or firmware(not shown). As described in detail below, the database 121 may providecentralized storage of characteristics associated with individuals,allowing interoperability between different elements of the businessresiding at different physical locations.

Server 101 may operate in a networked environment 100 supportingconnections to one or more remote computers, such as terminals 141 and151. The terminals 141 and 151 may be personal computers or servers thatinclude many or all of the elements described above relative to theserver 101. The network connections depicted in FIG. 1 include a localarea network (LAN) 125 and a wide area network (WAN) 129, but may alsoinclude other networks. When used in a LAN networking environment, thecomputer 101 is connected to the LAN 125 through a network interface oradapter 123. When used in a WAN networking environment, the server 101may include a modem 127 or other means for establishing communicationsover the WAN 129, such as the Internet 131. It will be appreciated thatthe network connections shown are illustrative and other means ofestablishing a communications link between the computers may be used.Furthermore, any of a number of different communication protocols, suchas TCP/IP, Ethernet, FTP, HTTP and the like, may be used withinnetworked environment 100.

Additionally, an application program 119 used by the server 101according to an illustrative embodiment of the disclosure may includecomputer executable instructions for invoking functionality related toproviding access authorization for facilities and networks.

Computing device 101 and/or terminals 141 or 151 may also be mobileterminals including various other components, such as a battery,speaker, and antennas (not shown).

The disclosure is operational with numerous other general purpose orspecial purpose computing system environments or configurations.Examples of well known computing systems, environments, and/orconfigurations that may be suitable for use with the disclosure include,but are not limited to, personal computers, server computers, hand-heldor laptop devices, multiprocessor systems, microprocessor-based systems,set top boxes, programmable consumer electronics, network PCs,minicomputers, mainframe computers, distributed computing environmentsthat include any of the above systems or devices, and the like.

The disclosure may be described in the general context ofcomputer-executable instructions, such as program modules, beingexecuted by a computer. Generally, program modules include routines,programs, objects, components, or data structures, that performparticular tasks or implement particular abstract data types. Thedisclosure may also be practiced in distributed computing environmentswhere tasks are performed by remote processing devices that are linkedthrough a communications network. In a distributed computingenvironment, program modules may be located in both local and remotecomputer storage media including memory storage devices.

Referring to FIG. 2, an illustrative system 200 for implementing methodsaccording to the present disclosure is shown. As illustrated, system 200may include one or more workstations 201. Workstations 201 may be localor remote, and are connected by one or more communications links 202 tocomputer network 203 that is linked via communications links 205 toserver 204. In system 200, server 204 may be any suitable server,processor, computer, or data processing device, or combination of thesame.

Computer network 203 may be any suitable computer network including theInternet, an intranet, a wide-area network (WAN), a local-area network(LAN), a wireless network, a digital subscriber line (DSL) network, aframe relay network, an asynchronous transfer mode (ATM) network, avirtual private network (VPN), or any combination of any of the same.Communications links 202 and 205 may be any communications linkssuitable for communicating between workstations 201 and server 204, suchas network links, dial-up links, wireless links, or hard-wired links.

The steps that follow in the Figures may be implemented by one or moreof the components in FIGS. 1 and 2 and/or other components, includingother computing devices.

FIG. 3 is an illustrative functional block diagram of a self-servicefinancial transaction device (SSFTD) 300. SSFTD 300 may include, forexample, an automated teller machine (ATM) or automated kiosk fordepositing (e.g., receiving a check for deposit in a user's account)and/or withdrawing (e.g., dispensing currency from a user's account)monetary funds, such as checks and cash, checking account balances(e.g., providing a total balance of a user's account), receiving cashadvances, and performing various other financial transactions. Whilewithdrawals from SSFTD 300 by a user are typically provided to the useras currency, deposits made in SSFTD 300 may be in the form of currency,checks, and other such forms.

As shown in FIG. 3, SSFTD 300 may include a computer 301, a hard drive302 or other computer-readable medium, a deposit unit 303, a withdrawalunit 304, a display 305, a printer 306, a keypad 307, a networkinterface 308, a removable media interface 309, a safe 310, a scanner313, and a card reader 315. Although computer 301 is labeled as a“computer,” any one or more of the other functional blocks in FIG. 3 mayalso be or include a computer. As understood, SSFTD 300 may include oneor more computers 301, hard drives 302, deposit units 303, withdrawalunits 304, displays 305, printers 306, key pads 307, network interfaces308, removable media interfaces 309, safes 310, scanners 313, and cardreaders 315.

The term “computer” as referred to herein broadly refers to anyelectronic, electro-optical, and/or mechanical device, or system ofmultiple physically separate or physically joined such devices, that isable to process and manipulate information, such as in the form of data.Non-limiting examples of a computer include one or more personalcomputers (e.g., desktop or laptop), servers, smart phones, personaldigital assistants (PDAs), television set top boxes, and/or a system ofthese in any combination or sub-combination. In addition, a givencomputer may be physically located completely in one location or may bedistributed amongst a plurality of locations (i.e., may implementdistributive computing). A computer may be or include a general-purposecomputer and/or a dedicated computer configured to perform only certainlimited functions.

A computer typically includes hardware that may execute software and/orbe configured in hardware to perform specific functions. The softwaremay be stored on a computer-readable medium in the form ofcomputer-readable instructions. A computer may read thosecomputer-readable instructions, and in response perform various steps asdefined by those computer-readable instructions. Thus, any functionsattributed to any of the functional blocks of FIG. 3 as described hereinmay be implemented, for example, by reading and executing suchcomputer-readable instructions for performing those functions, and/or byany hardware subsystem (e.g., a processor) from which the computer iscomposed. Moreover, steps or methods described herein may be implementedthrough computer-executable instructions stored on the aforementionedmemory (and memory 115 in a remote computing system.)

The term “computer-readable medium” as used herein includes not only asingle physical medium or single type of medium, but also a combinationof one or more physical media and/or types of media. Examples of acomputer-readable medium include, but are not limited to, one or morememory chips, hard drives (e.g., hard drive 302), optical discs (such asCDs or DVDs), magnetic discs, and magnetic tape drives. Acomputer-readable medium may be considered part of a larger device or itmay be itself removable from the device. For example, a commonly-usedremovable computer-readable medium is a universal serial bus (USB)memory stick that interfaces with a USB port of a device.

A computer-readable medium may store computer-readable instructions(e.g., software) and/or computer-readable data (i.e., information thatmay or may not be executable). In the present example, acomputer-readable medium (such as memory) may be included in any one ormore of the functional blocks shown in FIG. 3 and may storecomputer-executable instructions and/or data used by any of thosefunctional blocks. Alternatively or additionally, such acomputer-readable medium storing the data and/or software may bephysically separate from, yet accessible by, any of the functionalblocks shown in FIG. 3.

In an arrangement where SSFTD 300 may be an automated teller machine(ATM), computer 301 may be embodied as a personal computer and may beresponsible for the overall control of SSFTD 300. To perform suchcontrol, computer 301 may execute, for example, one or more softwareapplications, one or more device control programs, and one or moreoperating systems, each of which may be stored on hard drive 302, whichmay be a single physical hard drive or multiple physical hard drives.These various elements will be discussed in further detail below.

Hard drive 302 may be a single physical hard drive unit or may includemultiple physical hard drive units. Rather than, or in addition to, harddrive 302, SSFTD 300 may store data and/or computer-executableinstructions on one or more other types of computer-readable medium,such as an optical disc drive, a magnetic tape drive, and/or memorychips.

Deposit unit 303 may be responsible for physically receiving depositeditems such as currency and checks, for physically counting the depositeditems, for physically holding the deposited items in an escrow areaduring a deposit transaction, for calculating the value of the depositeditems, and for physically transferring the deposited items to safe 310when the transaction is complete.

Withdrawal unit 304 may be responsible for physically retrievingcurrency or other items from safe 310 during a withdrawal transaction,and for physically providing the retrieved currency to the user.

Display 305 may be responsible for displaying a visual user interface tothe user, and may also incorporate a touch screen capability forreceiving user input. Typical information that may be presented ondisplay 305 includes text and/or graphics representing the status of atransaction. Likewise, printer 306 may be responsible for presenting apaper printout containing information about a transaction.

Key pad 307 may include one or more buttons, switches, and/or otherphysical user input elements, and may be responsible for receiving userinput associated with a transaction. For example, key pad 307 mayinclude digit keys zero through nine and other function keys. Cardreader 315 may be any type of device that reads data from a card, suchas the magnetic strip on magnetic cards such as ATM/bank cards.

Network interface 308 (e.g., communications network transmitter) may beresponsible for data communication between SSFTD 300 and a remotecomputing system 101 over a network 312. The communication may beuni-directional or bi-directional. Network 312 may be a single networkor combination of multiple coupled networks, and may be wireless and/orwired. Examples of network 312, or portions thereof, include theInternet, a wired or wireless local area network, a satellitecommunication network, and various other data or communication networks.The data communicated from the SSFTD 300 to a remote computer 101 mayinclude, but is not limited to, transaction data, session data, and/oruser wait time data.

Removable media interface 309 may be responsible for reading from and/orwriting to a removable computer-readable medium 311, such as a USB key,a compact disc (CD), a floppy magnetic disc, or a portable hard drive.Removable media interface 309 may therefore include a physical port forplugging in or otherwise temporarily receiving removablecomputer-readable medium 311. This port may be physically part of, forinstance, the housing of computer 301. However, the port may be locatedelsewhere in or on SSFTD 300, such as on a rear housing of SSFTD 300that may be accessible to maintenance servicers of SSFTD 300 but notnecessarily to the general public. Regardless of the location of theport, data read from removable computer-readable medium 311 by removablemedia interface 309 may be provided to computer 301, and data providedby computer 301 may be written by removable media interface 309 tocomputer-readable medium 311.

Scanner 313 may include, for instance, a camera that is able to take adigital photograph of a check to produce one or more images representingthe front and/or back of the check. In addition to generating an imageof the check, scanner 313 may be further capable of reading magneticallyprinted information on the check, such as magnetic ink that is typicallyprinted on a check, and performing magnetic ink character recognition(MICR). Such MICR processes are well known. The data produced byperforming MICR that represents the recognized magnetic ink charactersis referred to herein as MICR data. Scanner 313 further may beconfigured to perform optical character recognition (OCR) on a check,which involves the translation of optically scanned text or writteninformation on the check into machine-encoded text that can be read byscanner 313.

In another aspect of the disclosure, a system (e.g., SSFTD 300 andsurrounding area) may include hardware (e.g., sensors, timers, oraudio/video recorders) and/or software components (e.g.,computer-executable instructions stored on non-transitory, tangiblecomputer-readable media) to assist in measuring and collecting variousreadings. The system may include a means for capturing a user's arrivetime and queue time while waiting for a SSFTD. For example, a videocamera may be installed in or in close proximity to the SSFTD (e.g.,physically outside of the SSFTD) to allow capture of information such asthe time when a user first gets in line to use a SSFTD and/or the totalamount of time the user waits before a SSFTD is available for his/heruse. In another example, enhanced optical sensors in combination with aninvisible scattered laser beam may be used to detect the presence ofusers in an area around the SSFTD and track their movement to determineuser wait time data. In yet another example, pressure sensors (e.g., ina floor mat upon which users in a queue might stand, or in an objectover which a vehicle may drive in a drive-up SSFTD) may be used tocapture a user's arrive time and queue time. In yet another example,video cameras installed at a retail location may be used to obtainadditional user insights and wait time tolerances. In addition, themeans for capturing may include a processor, memory, and/orcomputer-executable instructions to assist in analyzing the captureddata to actually calculate user wait time data.

In addition, the SSFTD 300 may collect transaction data and user waittime data resulting from a user's interaction at a SSFTD site. Examplesof transaction data include, but are not limited to, one or more of:transaction time (i.e., the time when the transaction started and/orended), transaction date (i.e., the date of the transaction and/or dayof the week), transaction type (e.g., deposit, withdrawal, balanceinquiry, or any other transaction type), unique card identifier (i.e.,any means to uniquely identify the user), and unique terminalidentifier. In some examples, the unique terminal identifier maycomprise information about whether the SSFTD is located inside oroutside, whether it is located on the premises of a financialinstitution, approach type (e.g., whether it is drive-up or walk-upSSFTD), and configuration information (e.g., whether the location has asingle-SSFTD or dual-SSFTD configuration, a single user queue with adual-SSFTD configuration, or separate queues with a dual-SSFTDconfiguration.) In some examples, a mapping file (e.g., a text or binaryfile) may identify each particular configuration that corresponds toeach unique terminal identifier. The SSFTD 300 or a remote computer 101may store/maintain the mapping file and compare each unique terminalidentifier to the mapping file to determine the configuration. In analternate embodiment, the unique terminal identifier may be coded suchthat a portion of the digits may indicate the type of configuration. Forexample, the last 3 digits of the unique terminal identifier may be setto “001” if the configuration is a single walk-up SSFTD, and “010” ifthe configuration is a single drive-up SSFTD, and so on.

Referring to FIG. 6, the user wait time data may include arrive time602, queue time 604 and/or dwell/leave time 610. The arrive time 602 maybe the time and date when a user gets into a queue to use a SSFTD, andthe queue time 604 may be the total time that the user waits in thequeue before the time he/she approaches 606 the SSFTD to begin one ormore transactions 608. While the system may collect data on a pertransaction basis during time 608, the system may later (or in nearreal-time) combine the numerous transaction data to form session data.The session data for a user may be later formed by identifyingconsecutive transactions (e.g., using the timestamp of each transaction)at the SSFTD with the same banking card (or other unique useridentifier). The session data (e.g., session time) more accuratelyrepresents the economies of scale that occurs when a user performsmultiple transaction during a visit to a SSFTD.

Finally, the dwell/leave time 610 may be the amount of time aftertransactions are completed that a user occupies the SSFTD 300. In theexample of a drive-up SSFTD, a user may linger after the transaction(e.g., on the cell phone and/or searching/organizing belonging in frontof the SSFTD before driving away), thus resulting in a longer period oftime that the machine is “in use” and unavailable to the next user. Inthe example of a walk-up SSFTD, a user may count and re-count dispensedcash after completing a transaction or may be organizing their belonginginto a purse after a transaction, before stepping away from the SSFTD.The enhanced modeling and business rules/metrics of the disclosurefactor in the total end to end user experience, including wasteddwell/leave time and queue time. A SSFTD capacity model based solely onutilization fails to properly account for a poor drive-up SSFTD userexperience. In the pure utilization model, single drive-up SSFTDs willinfrequently meet high utilization thresholds because that model failsto account for the sometimes noticeable user dwell time, which mayresult in time when a drive-up SSFTD is unavailable for use, but forpractical purposes, still in use, as illustrated in FIG. 6. As such, theenhanced model of this disclosure identifies updated thresholds fordrive-up SSFTDs that account for the user dwell time and result in animproved end to end user experience (e.g., greater likelihood that userwait time will be less for a great majority of users.) Based onempirical data collected and analyzed, in some embodiments, the userdwell time allows for a more accurate model of a single drive-up SSFTDbecause that configuration rarely shows SSFTD utilization over 75%, yetcustomer wait times, thus the end-to-end user experience, may be poor.

While the SSFTD 300 has been described in some embodiments as comprisingparticular components and/or memory storing particularcomputer-executable instructions, the disclosure contemplates one ormore components and/or memories being located outside of the SSFTD 300.For example, transaction data may be aggregated, sorted, and used todetermine session data at a remote computing system 101. In anotherembodiment, some SSFTDs might not include a means for capturing (e.g., avideo camera) a user's arrive time and queue time. Rather, these SSFTDsmay simply provide transaction data and/or session data to the remotecomputing system 101. The system may compensate for the lack of datawith respect to the particular SSFTD using heuristics and statisticaltechniques, including simulation models and Monte Carlo techniques,based on historical and current data collected from comparable SSFTDconfigurations (and other sources).

Referring to FIG. 8, aspects of the disclosure relate to methods andsystems 101 for using an enhanced model to simulate numerous scenariosfor each SSFTD configuration each hour and derive key outputs to modelthe complete end-to-end user experience. As a result, the systemdetermines when installation of additional SSFTDs (e.g., computingdevices 141, 151) may be desired at a location/site, and generatesrecommendations accordingly. The system may include a processor 103 andmemory 115 (e.g., database, data store, or other means for memory) tostore transaction-level data and other data about SSFTDs and an enhancedSSFTD user wait time model to identify appropriate recommendations andother outputs. In some embodiments, the system may group the transactiondata, session data, and/or user wait time data by SSFTD configuration toformulate a data set for use with an enhanced model for simulations withthe particular SSFTD configuration.

As shown in the table 800 of sample data, twelve users interacted with aSSFTD during a one-hour interval. The data from each user's sessionshows the various wait times for each user. The data from the table 800is used to generate an output (displayed at the bottom of FIG. 8) thatshows the average wait time per user and other statistics for the hour.These outputs may comprise the data set on which appropriate businessrules and metrics, such as user wait time service level agreement orutilization, may be applied. Some example of these outputs may include,but are not limited to queue lengths, user wait time, SSFTD utilization,transactions completed by type, average transaction duration by type,and others. Other examples of outputs include, but are not limited toaverage wait time over a predetermined time period, percentage of userswith wait time below a predetermined threshold, SSFTD utilization over apredetermined time period, and number of hours where SSFTD utilizationis over a predetermined threshold.

Specifically, disclosed herein is an enhanced modeling of SSFTDutilization that incorporates user behavior (e.g., the full end to enduser experience) to simulate user wait time. The enhanced modelidentifies capacity constrained SSFTD sites where the user experience ispoor. While prior SSFTD modeling attempts simply identified most highlyutilized SSFTDs, those did not always capture the SSFTD sites where userexperience was poor. Through the enhanced model a specific correlationbetween user wait time and SSFTD utilization is identified. A long userwait time correlates with high SSFTD utilization. Additionally, theenhanced model accounts for outliers with high peak time trafficpatterns and low monthly volume.

Referring to FIG. 7, the configuration of the SSFTD location and the waythe customer line forms are at least two factors driving the differencein user wait time. For example in table 700, a dual walk-up SSFTDsubstantially reduces wait time as compared to a single walk-up SSFTD.Data such as that displayed in tables 700 and 800 may be collected andsaved in a data store at a remote computing system for analysis and usein an enhanced model simulating the SSFTD configuration. Such enhancedmodel allow identification of the discovery that two side-by-side SSFTDswith one customer line serve more customers faster than two SSFTDs indifferent locations with separate lines. Moreover, different types(e.g., drive-up versus walk-up) of SSFTDs require different machineutilization characteristics to maintain good end-to-end user experience.Other discoveries of business rules for the configuration and placementof SSFTD include those described below.

For example, referring to FIGS. 5A and 5B, sample data from one or moresingle drive-up ATMs (e.g., SSFTDs) is displayed. FIG. 5A shows thehourly utilization rate of the SSFTD as compared to the percentage ofusers that wait five minutes or less to use the single drive-up SSFTD.With a desired predetermined threshold of 80% for percentage of userswith wait times of five minutes or less, the data points from FIG. 5Aindicate that a hourly SSFTD utilization rate of approximately 55% isdesirable. Furthermore, referring to FIG. 5B, the 80% thresholdcorresponds to approximately 140 hours where SSFTD utilization exceeded55%. As such, the enhanced model provides for the creation andimplementation of a business rule that if at a single drive-up SSFTD,the SSTFD machine utilization exceeds 55% for more than 140 hours in amonth, then the system, based on the enhanced model, may recommendadjusting the configuration of the SSFTD to replace the single drive-upwith a dual drive-up configuration. The enhanced model allows for therecommendation to be based on machine utilization statistics, however,the end-to-end user experience is considered in the recommendation(e.g., 80% of users will experience 0-5 minutes of wait time). Oneskilled in the art will appreciate that the sample data of FIG. 5A andFIG. 5B may be used to set different user wait thresholds such that evenless percentage of users will experience wait times greater than 5minutes.

In other examples, sample data may be collected for other SSFTDconfigurations such that outputs and recommendations may be providedaccordingly. For example, if hourly SSFTD utilization is above 60% butthe number of hours the utilization threshold of 60% is exceeded is lessthan 110 hours in a month, then the system, based on the enhanced model,may recommend that only one walk-up SSFTD is necessary to maintain asuccessful end-to-end user experience. In another example, if the hourlySSFTD utilization is above 70% and the number of hours the utilizationthreshold of 70% is exceeded is over 120 hours, then the system mayrecommend a 2+ walk-up SSFTD. In yet another example, for a singledrive-up SSFTD, if hourly SSFTD utilization is above 55% but the numberof hours the utilization threshold of 55% is exceeded is less than 140hours in a month, then the system, based on the enhanced model, mayrecommend that only one drive-up SSFTD is necessary to maintain asuccessful end-to-end user experience. In yet another example, if hourlySSFTD utilization is above 65% and the number of hours the utilizationthreshold of 65% is exceeded is greater than 110 hours in a month, thenthe system, based on the enhanced model, may recommend that a 2+drive-up SSFTD may be desirable to maintain a successful end-to-end userexperience.

While the examples above provide numerous parameters for the collection,analysis, and/or recommendation of adjustments to the configuration/typeof SSFTDs, this disclosure also contemplates other combinations andparameters. For example, the enhance model may, in some embodiments,calculate utilization values for time intervals other than one hour. Forexample, utilization data may be calculated and rated based on 30-minuteintervals, two-hour intervals, or other intervals.

Referring to FIG. 5B, other aspects of the disclosure may assist in theearlier identification of a problematic SSFTD site through analysis ofcollected measurements as compared to statistical measurements in theenhanced model. For example, the data points in the “watch” rectangulararea in the lower-left of the graph may indicate a malfunctioning SSFTDbecause although machine utilization may be at the desired 55%threshold, if the percentage of users waiting longer than 5 minutes ishigh, then this may be an indication that something is causingunnecessary delays between uses. The system may send a recommendation topersonnel responsible for the maintenance of the SSFTD that a problemmay be occurring at the SSFTD site.

FIG. 4 illustrates an example method performed by a remote computingsystem 101 in communication with a SSFTD 300 in accordance with aspectsof the disclosure. The system 101 may receive (in step 402), from aSSFTD 300, collected data, where the collected data comprising one ormore of transaction data, session data, and user wait time data. In step404, the computer system 101 may identify the SSFTD configuration usingthe unique terminal identifier from the collected data. In step 406, thecomputer system 101 may create an enhanced user wait time model bygrouping some or all of the collected data corresponding to anidentified configuration. The grouped data may be used to determine arelationship between hourly user wait time data and hourly deviceutilization, as depicted in FIG. 5A. Moreover, the grouped data may beused to determine a relationship between monthly user wait time data andmonthly device utilization, as depicted in FIG. 5B. In step 408, thecomputer system 101 may generate outputs, including recommendations,based on the enhanced user wait time model. The recommendations may bebased on predetermined thresholds (e.g., device utilization thresholdsor user wait time thresholds) and the enhanced user wait time model. Thepredetermined thresholds may be set based on a desired goal for userwait time (e.g., a goal of 80% of users experiencing less than 5 minutesof wait time). In step 410, the computer system 101 may cause (e.g.,through a recommendation message sent to an administrator or capacityplanning department or displayed on a graphical user interface fordisplay) a configuration of an SSFTD to be adjusted based on thegenerated outputs and the predetermined thresholds. The adjustments tothe configuration of SSFTDs may include, but are not limited toreplacing a single walk-up with a dual walk-up, replacing a dual walk-upwith a single walk-up, replacing a single drive-up with a dual drive-up,replacing a dual drive-up with a single drive-up, and/or consolidatingtwo single walk-ups at two sites into a single dual walk-up. Afterreview of the entirety disclosed herein, one skilled in the art willappreciate that the predetermined thresholds may be tweaked as desiredto obtain business objectives of less user wait time or greater deviceutilization.

Although specific examples of carrying out the aspects of the disclosurehave been described, those skilled in the art will appreciate that thereare numerous variations and permutations of the above-described systemsand methods that are contained within the spirit and scope of thedisclosure as set forth in the appended claims. Additionally, numerousother embodiments, modifications and variations within the scope andspirit of the appended claims will occur to persons of ordinary skill inthe art from a review of this disclosure.

1. A system comprising: a self-service financial transaction deviceconfigured to at least one of: receive a check for deposit in a user'saccount, dispense currency from the user's account, and provide totalbalance of the user's account; at least one processor; and at least onememory having stored therein computer-executable instructions, that whenexecuted by the at least one processor, cause the system to perform amethod of: collecting transaction data resulting from the user'sinteraction with the self-service financial transaction device, whereinthe transaction data includes transaction time, transaction date,transaction type, unique card identifier, and unique terminalidentifier; collecting user wait time data; and combining transactiondata to form session data based on consecutive transactions at theself-service financial transaction device with the same unique cardidentifier; and a communications network transmitter configured totransmit the collected transaction data, the session data, and the userwait time data to a remote computer, wherein the remote computercomprises an enhanced model determined using the transaction data,session data, and user wait time data, and further wherein the remotecomputer is configured to generate outputs based on the enhanced model,wherein the outputs comprise at least one of: average wait time over apredetermined time period, percentage of users with wait time below apredetermined threshold, self-service financial transaction deviceutilization over a predetermined time period, and number of hours whereself-service financial transaction device utilization is over apredetermined threshold, and wherein the enhanced model groups thetransaction data, session data, and user wait time data by self-servicefinancial transaction device configuration, wherein the remote computercauses configuration of the self-service financial transaction device tobe adjusted based on the generated outputs and predetermined user waitthresholds, and further wherein the configuration of the self-servicefinancial transaction device is adjusted from a single walk-up to a dualwalk-up when the hourly device utilization is over 60% for over 110hours in a month in order to keep user wait time within 5 minutes for85% of users.
 2. The system of claim 1, comprising: a means forcapturing a user's arrive time and queue time.
 3. The system of claim 2,wherein the means for capturing comprises at least a video camera, theat least one processor, and the at least one memory having storedtherein computer-executable instructions.
 4. The system of claim 1,wherein the unique terminal identifier comprises information aboutwhether the self-service financial transaction device is located insideor outside, whether it is located on the premises of a financialinstitution, approach type, and configuration.
 5. The system of claim 1,wherein the communications network transmitter includes a wirelesstransmitter configured to transmit the collected transaction data andthe session data over a wireless network.
 6. The system of claim 1,wherein the self-service financial transaction device is an automatedteller machine.
 7. A method comprising: receiving, from a self-servicefinancial transaction device, collected data, the collected datacomprising transaction data, session data, and user wait time data, andwherein the transaction data comprises transaction time, transactiondate, transaction type, unique card identifier, and unique terminalidentifier, and wherein the user wait time data comprises a user'sarrive time and queue time; identifying, by a computer, a self-servicefinancial transaction device configuration using the unique terminalidentifier, wherein the configuration comprises at least one of: singlewalk-up, dual walk-up with single user queue, dual walk-up with dualuser queue, single drive-up, dual drive-up with single user queue, anddual drive-up with dual user queue; grouping, by the computer, thecollected data corresponding to an identified configuration to create anenhanced user wait time model; generating, by the computer, outputsbased on the enhanced user wait time model, where the outputs compriseat least one of: average wait time over a predetermined time period,percentage of users with wait time below a predetermined threshold,self-service financial transaction device utilization over apredetermined time period, and number of hours where self-servicefinancial transaction device utilization is over a predeterminedthreshold; and causing configuration of the self-service financialtransaction device to be adjusted based on the generated outputs andpredetermined user wait thresholds wherein the configuration of theself-service financial transaction device is adjusted from a singlewalk-up to a dual walk-up when the hourly device utilization is over 60%for over 110 hours in a month in order to keep user wait time within 5minutes for 85% of users.
 8. The method of claim 7, wherein theidentifying the configuration using the unique terminal identifiercomprises comparing the unique terminal identifier against a mappingfile to determine its configuration.
 9. The method of claim 7, furthercomprising: determining a relationship between hourly user wait timedata and hourly device utilization; determining a relationship betweenmonthly user wait time data and monthly device utilization; and settingthe predetermined user wait thresholds based on a desired goal for userwait time.
 10. The method of claim 7, wherein the self-service financialtransaction device is an automated teller machine.
 11. One or morenon-transitory computer-readable media storing computer-readableinstructions that, when executed by at least one computer, cause the atleast one computer to perform a method of: identifying, by a computer, aconfiguration of one or more self-service financial transaction devicesusing a unique terminal identifier, wherein the configuration comprisesat least one of: single walk-up, dual walk-up with single user queue,dual walk-up with dual user queue, single drive-up, dual drive-up withsingle user queue, and dual drive-up with dual user queue; grouping, bythe computer, collected data corresponding to an identifiedconfiguration to create an enhanced user wait time model, the collecteddata comprising transaction data, session data, and user wait time data,and wherein the transaction data comprises transaction time, transactiondate, transaction type, unique card identifier, and unique terminalidentifier, and wherein the user wait time data comprises a user'sarrive time and queue time; and generating, by the computer, arecommendation for adjusting the configuration of the one or moreself-service financial transaction devices based on the enhanced userwait time model wherein the recommendation for adjusting theconfiguration of the one or more self-service financial transactiondevices is to replace a single walk-up to a dual walk-up when the hourlydevice utilization of the single walk-up is over 60% for over 110 hoursin a month.
 12. The one or more non-transitory computer-readable mediaof claim 11, the computer-readable instructions that, when executed byat least one computer, further cause the at least one computer toperform: determining, by the computer, a relationship between hourlyuser wait time data and hourly device utilization; determining, by thecomputer, a relationship between monthly user wait time data and monthlydevice utilization; and setting, by the computer, the predetermined userwait thresholds based on a desired goal for user wait time.
 13. The oneor more non-transitory computer-readable media of claim 11, wherein theoutputs comprise at least one of: average wait time over a predeterminedtime period, percentage of users with wait time below a predeterminedthreshold, self-service financial transaction device utilization over apredetermined time period, and number of hours where self-servicefinancial transaction device utilization is over a predeterminedthreshold.
 14. A method comprising: receiving, from a self-servicefinancial transaction device, collected data, the collected datacomprising transaction data, session data, and user wait time data, andwherein the transaction data comprises transaction time, transactiondate, transaction type, unique card identifier, and unique terminalidentifier, and wherein the user wait time data comprises a user'sarrive time and queue time; identifying, by a computer, a self-servicefinancial transaction device configuration using the unique terminalidentifier, wherein the configuration comprises at least one of: singlewalk-up, dual walk-up with single user queue, dual walk-up with dualuser queue, single drive-up, dual drive-up with single user queue, anddual drive-up with dual user queue; grouping, by the computer, thecollected data corresponding to an identified configuration to create anenhanced user wait time model; generating, by the computer, outputsbased on the enhanced user wait time model, where the outputs compriseat least one of: average wait time over a predetermined time period,percentage of users with wait time below a predetermined threshold,self-service financial transaction device utilization over apredetermined time period, and number of hours where self-servicefinancial transaction device utilization is over a predeterminedthreshold; and causing configuration of the self-service financialtransaction device to be adjusted based on the generated outputs andpredetermined user wait thresholds wherein the configuration of theself-service financial transaction device is adjusted from a singledrive-up to a dual drive-up when the hourly device utilization is over55% for over 140 hours in a month in order to keep user wait time within5 minutes for 80% of users.
 15. The method of claim 14, wherein theidentifying the configuration using the unique terminal identifiercomprises comparing the unique terminal identifier against a mappingfile to determine its configuration.
 16. The method of claim 14, furthercomprising: determining a relationship between hourly user wait timedata and hourly device utilization; determining a relationship betweenmonthly user wait time data and monthly device utilization; and settingthe predetermined user wait thresholds based on a desired goal for userwait time.
 17. The method of claim 14, wherein the self-servicefinancial transaction device is an automated teller machine.